Cohort-Based User Interaction Data Analysis System
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Solution Overview
Problem
Current systems lack effective methods for cohort-based analysis and visualization of user interaction data across multiple users and software applications, limiting insights into user interaction patterns, feature usage, and software performance.
Innovation Solution
A computer system that aggregates user interaction data from multiple users and software applications, allowing operators to create cohorts, apply filters, and generate interactive visualizations such as tables, graphs, and bar graphs to analyze user interactions on a user-by-user or group-by-group basis, providing real-time insights into usage patterns, performance, and crashes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If user interaction data is aggregated across many users for analysis, then comprehensive insights into user interaction patterns can be obtained, but the complexity of data processing and visualization increases
Solution Approach 1:
The patent segments user interaction data into cohorts based on shared characteristics, time periods, or behaviors. This segmentation allows the system to manage complex aggregated data by breaking it into manageable groups, enabling detailed analysis of specific user segments while maintaining overall comprehensive insights without overwhelming processing complexity
Solution Approach 2:
The patent introduces cohort-based grouping as an additional dimension for organizing user interaction data. By adding this categorical dimension, the system transforms raw aggregated data into structured cohort-specific datasets, making the data more manageable and enabling multi-level analysis from both individual cohort and overall aggregate perspectives
2Measurement precision
If cohort-based analysis is implemented with multiple user groups, then detailed user interaction insights can be obtained, but the time required for data processing increases
Solution Approach 1:
The patent performs preliminary actions by pre-defining cohorts and pre-processing user interaction data into cohort-specific datasets before detailed analysis is required. This advance preparation stores processed cohort data in accessible formats, so when analysis is needed, the system can quickly retrieve and analyze pre-organized data rather than processing raw data from scratch each time
Solution Approach 2:
The patent changes data organization parameters by transforming user interaction data from individual-user format to cohort-aggregated format with relevant metrics. This parameter transformation occurs in advance, converting raw interaction events into pre-calculated cohort statistics that can be rapidly analyzed and visualized without repeating computationally intensive calculations
Data Source
AI summary
An interactive, customizable, user interaction data analysis system is disclosed. The system may be configured to provide cohort-based analysis and/or graphical visualizations of user interaction data to a system operator. User interaction data may be obtained, for example, as users interact with one or more software applications. In various embodiments, interactive and customizable visualizations and analyses provided by the system may be based on user interaction data aggregated across groups of users (also referred to as cohorts of users), across particular time frames, and/or from particular software and/or computer-based applications. According to various embodiments, the system may enable insights into, for example, user interaction patterns, the frequency of software application features accessed, the performance of various aspects of software applications, and/or crashes of software applications, among others.